Small and dim infrared moving target detection based on spatial–temporal saliency

Abstract

Infrared target detection is a significant work in military, high accuracy and high speed are the essential capabilities for precise guidance. With limited conditions, making full use of spatial–temporal information can really improve performance. This article studied small and dim infrared moving target detection based on sequence images. Quaternion Fourier Transform is an efficient method of visual saliency. To make this algorithm more accurate, we introduced four preprocessing feature map as input channels for quaternion. They are selective inter frame difference, fuzzy-based morphology filter, joint local gradient and gray contrast measure and temporal-constrained Gaussian curvature filter. All of them aim to highlight small-dim target and help to construct saliency map. Simultaneously, a trajectory constraint is introduced to reduce false alarm rate. Compared with single-frame based methods and multi-frames based methods, our novel algorithm performed better on balancing time consuming and detection precision.